Building Risk Models and Feedback Systems Using Large Volumes of Automobile Telematics Data

More and more vehicles are outfitted with telematics (e.g. Global Positioning System (GPS)) devices that allow real time data to be collected on driver behaviour. This includes, for example, your location, how long you’ve been driving, your pattern of acceleration and braking, your cornering, and other factors. This project will explore the best way to use such streaming telematics data from automobiles to assess accident risk and improve driver behaviour. We plan to build validated models that can be used to quantify the expected risk as well as develop systems that provide effective feedback to drivers to reduce risky behaviour. Such models and systems will provide insurance companies a competitive advantage allowing them to better assess risk, and thus state insurance rates, as well as reduce risks for their clients and thus improve safety generally on Ontario roads.

Faculty Supervisor:

Stefan Steiner

Student:

Partner:

Intelligent Mechatronic Systems Inc;University of Waterloo

Discipline:

Mathematics

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program: